Month April 2016

Here I’ve been laboring under the assumption that the 2015 Dietary Guidelines tell the American public to eat a diet lower in fat (because we eat “too much” of it now) and higher in carbohydrate (especially from whole grains like whole wheat–because we don’t eat “enough” of those now), to eat less salt, and to “eat as little dietary cholesterol as possible.” But according to a document recently released from a source at the Center for Nutrition Policy and Promotion (CNPP) that isn’t what the Guidelines say. Or at least not exactly. Maybe.

The good folks at CNPP were asked to respond to Kris Gunnar’s list of “20 Mainstream Nutrition Myths (Debunked by Science)” with the idea being that the Guidelines are about as “mainstream” as nutrition advice gets. The hope was that, if the good folks at CNPP could explain why their advice is ostensibly “backed by science” and yet is “debunked by science,” we would all sleep a little better at night, even if we still insisted on eating bacon and eggs in the morning.

The good folks at CNPP rose to the challenge and cleared things right up. But, to quote the inimitable if soporific Crosby, Stills and Nash, “just beneath the surface of the mud, there’s more mud. Surprise.”

Below, I’ve restated their responses as dietary guidance arranged in an order that I found amusing. The number of the corresponding “Myth” from Kris Gunnars is given as well, so that those of you with split screens or dual monitors can play along at home.

According to the good folks at CNPP, the 2015 Dietary Guidelines for Americans:

do not recommend Americans eat a diet low in total fats or high in carbohydrates, particularly from grains. (Myth 1)

I know what you’re thinking. Adele’s mind has finally blown a gasket from reading all those big words they have in grad school. I’m not going to argue that point, but you can check the CNPP’s response for yourself right here.

This response also acknowledges that current scientific evidence regarding the reduction of full-fat dairy is contradictory (Myth 10) and that a variety of eating patterns can produce weight loss (Myth 8). It also says that 3-5 cups of coffee a day can be part of a healthy diet (Myth 7)–hallafreakinlujah– but whole wheat products? Meh (Myth 5).

I can see the helpful public health messages now:

You should not avoid egg yolks, but you should eat as little dietary cholesterol as possible, even though dietary cholesterol consumption is not linked to heart disease.

You don’t need to choose low-fat foods, just choose fat-free or low-fat milk, yogurt, and cheese even though it might not actually help you avoid chronic disease .

You should shift to lower sodium consumption without restricting your intake of sodium.

What’s going on here?

Good question. Perhaps the good folks at CNPP didn’t actually read the Dietary Guidelines this time around. Who, except for me, has that kind of time? Or maybe they had a hard time finding them. Once you get to the health.gov/dietaryguidelines/ site, you have to click through 3 menus or links before you get to the actual guidelines (try it), which are a swarm of footnotes and “see more” hyperlinks. Even Marion Nestle complained about how hard all those “annoying drop-down boxes” are to navigate. It’s possible the good folks at CNPP just assumed that the other good folks over at DHHS–responsible for Guidelines online labyrinth–were paying attention so they didn’t have to.

Or maybe it means that it’s actually really hard to get words to say what you want them to say without them saying other things that you don’t want them to say. And this is especially difficult when you are asked to make sweeping recommendations based on a weak scientific evidence base that both supports and contradicts past guidance, which you can’t contradict even when you can’t support it, because, then what?

No wonder the good folks at CNPP are having a hard time getting their story straight.

To tell the truth, I have a lot of sympathy for the message-makers there at the USDA. We created the Dietary Guidelines 35 years ago assuming zero potential negative consequences. True, the scientific evidence didn’t strongly support the recommendations, but whatever. Whether they followed the recommendations or not, hey, the health trajectory of Americans couldn’t get any worse, could it? We knew the Guidelines would significantly impact the food industry, but that could only be a good thing, right? And we meant for Guidelines to set the direction for nutrition research, but since science is only about facts and never about politics or funding, any errors or biases in our original rationale would be quickly discovered and corrected, no?

Now it seems pretty clear that we might have spent a little more time thinking through the whole “Let’s make sweeping dietary recommendations that are meant to apply to every single American alive over the age of 2 as a method of preventing every single major chronic disease known to humankind “thing before shrugging our shoulders and saying “Oh, no worries. It will all work out.” Now the folks at the USDA have used up their wishes and are left trying to stuff the genie back in the bottle with nothing but semantics and poor website design.

It's nice to share:

Like this:

One of the major problems in nutritional epidemiology is that we have a hard time measuring things that we are supposed to be measuring in order to say anything meaningful about relationships between diet and chronic disease. You know, things like how much people are actually eating or how much physical activity they really do get.

Today I had the opportunity to hear Walter Willett, king daddy of the field of nutritional epidemiology, speak on just this dilemma (and yes, he still has that sweet ‘stache). Introduced as having received “too many awards to mention,” W began his talk–“Energy Balance and Beyond: The Power and Limits of Dietary Data”–by addressing the recent unpleasantness raised by researchers who have suggested that the dietary data that we collect simply isn’t worth analyzing (Archer, Pavela, & Lavie 2015; Dhurandhar et al. 2015).

Having been recently immersed in my rhetoric of science readings, I noted that W started right off with some perfunctory boundary work, as way of indicating who was “in” and who was “out” when it came to credibility: He noted that the investigators questioning the value of dietary self-reports are “funded by Coca-cola,” and even the ones that are “pretty good scientists” are “not epidemiologists” and therefore “a little bit naive.” So much for evaluating the data and the arguments on their own merits.

Then he trotted out the “slippery slope” argument: If we throw out self-reported dietary data because it is wildly inaccurate, then not only do we have to “throw out the Dietary Guidelines” (heaven forfend!), but we’d have to throw out occupational safety and drug trial data also–because these are often based on self-reports. Certainly, there’s very little difference between reporting on events in your workplace or what side effects you might have in response to a pill you’re taking and reporting on what you remember eating over the course of the past year.

Then he got down to the nitty-gritty. The reason your Average American is fat is, to put it bluntly, because of math:

2500 kcals/day x 1% = 25 kcals/day

25 kcals/day x 365 days/year = 9125 kcals/year

9125 kcals/year = about 1kg of weight gain/year

Of course, the Average American only gains (on average) about 0.5 kg/year, but W easily explained the discrepancy: We gain weight, but then we have to expend more energy dragging our fat asses around–my words, not his–so we don’t gain as much weight as we would, but then the increased energy expenditure makes us hungry, so we eat more, so we gain weight, ad infinitum, only not, because we seem to plateau, but then, well, there’s that.

So here’s the $64,000 (or really a few hundred million in grant money) question: How good are we at measuring the 1% (or less) difference between “energy in” and “energy out” that we see expressed as weight gain in the population?

The answer, according to the man himself? Not very.

W then showed a comparison of a set of methods to measure “energy in,” along with their coefficient of variation (you can get the technical explanation here, but it is–simplistically–a measure of the amount of variability in your data; long story short: larger numbers = more variability, less precision and smaller numbers = less variability, more precision).

It looked something like this:

Method

Co-efficient of variation

Food frequency questionaire (FFQ)

15%

Diet record

13%

24-hour diet recall interview

28%

Doubly-labeled water (DLW)

9%

Weight

3%

What W made clear is that, if you want to know whether–or to what extent–Americans are indeed eating more and moving less, you can’t measure “energy in” using FFQs, diet records, and interviews and expect to get anywhere near that “1% of calories” accuracy you’re looking for. You can’t even rely on doubly-labeled water, typically considered to be a biomarker measurement with a high degree of precision. In fact, W made the point that DLW samples sent out to different labs would come back with results that differed by up to 50%.

W went on to explain that we have similar difficulties measuring “energy out,” with our very best measurements having a coefficient of variation of nearly 20%.

So in other words, or actually in W’s exact words:

“Weight is the best measure of energy balance.”

Wait? Weight?

As far as I can figure it, using weight as a way of “measuring” (and I use that term loosely) energy balance creates a theoretical–if not a methodological–situation that is, in a word, unfalsifiable. Or–in another word–bogus.

“Weight gain results when the things that we think cause weight gain happen, thus proving that those things have happened.”

At least one of the reasons for attempting to measure “energy in” and “energy out” is to find out whether or not it makes sense to attribute weight gain (or loss) to the differences between them. Instead, W is saying, we can know all we really need to know about how much people eat or move or both, because, voila, weight.

This is like saying, even though traces of tooth fairy fingerprints, footprints, or fiber samples are extremely difficult to obtain, we can reliably determine the existence of tooth fairies by the presence of quarters under your pillow.

Not only does this completely disregard the ever-growing list of things that may also contribute to weight gain/loss over time,* but it contradicts W’s own assertion just moments later that–even though we can’t do it very accurately–a good reason for attempting to measure total energy intake is that it can act as a “crude measure of physical activity.”

One the one hand, W is saying we can estimate how active you are by finding out how much you eat because people who eat more are also likely to be more active–that’s why they eat more–and people who eat less are typically less active–that’s why they don’t eat as much–with the implication being that “energy in” and “energy out” are positively related; as one changes, the other changes in the same direction.

On the other hand, he’s saying these two variables are completely independent of each other. Eating more doesn’t imply you move more; moving less doesn’t imply you eat less. And the way we know that these two variables are disconnected in any given Average American is, voila again, weight.

At this point, it was hard not to be completely distracted by the cognitive dissonance ringing through the room.

I did hang on long enough to hear W say that we shouldn’t really be worried about energy intake anyway because what really matters is diet quality, which, by the way, we can’t measure accurately either.

With all due respect, all I could think of is that while Emperor W may not be completely without clothes, he was definitely down to boxer shorts today.

In an auditorium full of really smart people, I cannot have been the only person thinking that W and his data looked a little over-exposed. But–as we saw with the circumstances revealed by the Ramsden and Zamora paper last week–it can be hard to contradict a famous colleague, and in nutritional epidemiology, no one is famouser than W. It may be even harder, I suppose, when he is an invited guest and an apparently nice fellow. The Q&A was respectful and polite. Difficult as it is to believe, even I kept my mouth shut.

I know science sometimes advances one funeral at a time, and I truly wish W a long and happy life. But maybe he’ll start to get a little chilly there in his boxers and start thinking about retiring someplace warm. Soon.

It's nice to share:

Like this:

I’m not a conspiracy theorist. Really. But as I wade through the thicket of science studies and rhetoric of science readings I have on my desk, I am more and more impressed with the power of paradigmatic thinking to distort how scientific knowledge is produced and disseminated.

Daisy Zamora and company have once again climbed in their wayback machine to reanalyze data from the Minnesota Coronary Survey, which began in 1968. The vegetable oil intervention reduced saturated fat intake by about half and cholesterol consumption by about two-thirds, while nearly tripling the intake of polyunsaturated fat. Surprise, surprise–they found that although the vegetable oil intervention reduced cholesterol levels, the intervention also led to more heart attacks and increased risk of death. [The press release on the study is here; the study itself is here.]

Let me just add that the original study outcomes–which did not support the diet-heart hypothesis even then–were not published until many years after the study ended, in fact, after its primary investigator retired.

Zamora and her co-investigators politely refer to these sort of anomalies as “incomplete publication,” as in:

“… incomplete publication of important data has
contributed to the overestimation of benefits – and the underestimation of potential risks – of replacing
saturated fat with vegetable oils rich in linoleic acid.”

All I want to say, before going back and burying my head once again in my books, is that